API

This is the API documentation for PIPE.

pipe Package

Functions

aperture(shape[, radius, xc, yc])	Returns a boolean 2D-array of the same dimensions as frame with True inside radius from (xc, yc), and False outside.
attitude(filename)	Reads the CHEOPS attitude file and puts the data into a N-by-4 array with spacecraft mjd, ra, dev, and roll angle.
cent_flux(cube)	Compute center of pixel values for cube of rectangular frames.
check_low(val[, clip, niter])	Filters values lower more than clip from the average (iterates niter times).
check_mask(mask_cube, apt[, clip, niter])	Checks the number of masked pixels for each mask of an array, and de-selects those frames that deviate more than clip sigma from the average.
check_motion(xc[, lowfrac])	Selects frames with positions after and before that are fairly consistent, with the goal to select frames with little motion blur.
check_pos(xc, yc[, clip, niter])	Filters positions deviating more than clip from the median (iterates niter times).
check_val(val[, clip, niter])	Filters values in array deviating more than clip from the average (iterates niter times).
clean_cube2D(data_cube, mask, apt)	Cleans all bad pixels as defined by mask (2D or 3D) inside aperture apt, by averaging neighbouring pixels in spatial dimensions (not time).
cube_apt(shape, radius, xc, yc)	Returns a cube with apertures for each plane along 0-axis defined by 1D-arrays xc and yc and constant radius.
datacube(filename[, frame_range])	Read CHEOPS datacube format, either subarray or imagettes.
derotate_position(xroll, yroll, rolldegs)	Function that de-rotates coordinates according to roll angle (in degrees)
flatfield(filename, Teff, offset, size)	Reads the flatfield cube and interpolates the flatfield temperatures to the given temperature.
gain(file_hk, file_gain)	Compute gain using HK parameters and the gain reference table Returns gain in units of e/ADU
imagette_offset(filename[, frame_range])	Returns the first imagette offset from an imagette fits-file cube; first offset is relative to full array, second offset is relative to subarray
integrate_psf(psf_fun[, radius])	Computes the flux of the psf inside radius.
interp_cube(t, t0, datacube0)	Resample planes from datacube, no extrapolation
interp_cube_ext(t, t0, datacube0)	Resample planes from datacube, with extrapolation
mad(series)	Compute normalised mean absolute deviation (MAD) for an array, return in ppm
make_maskcube(data_cube, noise_cube, model_cube)	Find pixels that deviate too much from fitted models, and produce a cube of masks.
mjd2bjd(filename)
multi_cent_binary_psf(psf_spline, cube, ...)	Use a PSF to find the best matching centres in a cube.
multi_cent_binary_psf_fix(psf_spline, cube, ...)	Use a PSF to find the best matching centres in a cube, using initial guessed positions and a fixed separation (dx, dy).
multi_cent_psf(psf_spline, cube, noise_cube, ...)	Use a PSF to find the best matching centres in a cube.
multi_psf_fit(psf_list, data_cube, ...[, ...])	Fit a defined PSF to a frame by constructing a matrix of offsets.
multi_psf_fit_binary(psf_list0, psf_list1, ...)	Fit two PSFs independently to both components of a binary, in a similar way as the regular multi_psf.fit function described above.
noise(debias, ron_elec[, e_per_ADU])	Computes the photon + read-out noise of a bias subtracted frame (or cube).
nonlinear(filename)	Reads the non-linear correction from a text file with ADU vs multiplicative correction.
pix_mat(datacube, noisecube, xc, yc, mask[, ...])	Turn a data cube into a pixel matrix with columns y-coordinate, x-coordinate, pixel value, pixel value noise the mask can either be a 2D plane or 3D cube (True = select, False mask out).
psf_noise(source_model, ron_elec[, e_per_ADU])	Uses a source model (PSF*scale+background) of the source to compute the photon + read-out noise.
psf_phot_cube(data_cube, noise_cube, ...)	Use defined PSF to integrate flux and derive error.
read_dark(darkpath, mjd, offset, size)	Traverses darkpath directory, looking for all dark current files and picks the one closest in time
read_mask(filename)	Reads a predefined mask saved as a fits file, returns numpy array
read_ron(filename)	Reads the readout noise table entry from the CHEOPS calibratared subarray cube file.
resample_attitude(obs_mjd, exp_time, attitude)	Resamples table of attitude data (RA, DEC, ROLL, DROLL) to the midtimes of the observations of duration exp_time Note: exptime in seconds, mjd in days, DROLL is change in roll angle during exposure
resample_imagette_time(sa_time, nexp)	Equidistantly distributes nexp exposures over the sa_time data points.
rotate_position(x, y, rolldeg)	Function that rotates coordinates according to roll angle (in degrees)
rough_contrast(cube[, radius, mask])	Computes a rouch contrast (flux difference) between pixels inside aperture and outside aperture, for each frame.
save_binary_eigen_fits(filename, t, bjd, ...)	Save lightcurve data from both componentes of a binary, as defined by arguments to fits table in binary format.
save_eigen_fits(filename, t, bjd, sc, err, ...)	Save lightcurve data as defined by arguments to fits table in binary format.
sigma_clip(data[, clip, niter])	A simple 1D sigma-clipping routine that returns a boolean array of indices to non-clipped data
starcat(filename, colstr[, entry])	Reads star catalogue file and returns value for column string colstr and entry row
sub_image_indices(offset, size)	Helper function that computes index ranges given a 2D offset and a 2D size
thermFront_2(filename)	Reads frontTemp_2 sensor data from the CHEOPS raw file.

Classes

PipeControl(pipe_params)
PipeLog([logfile, verbosity])	Keeps track of tima and messages to the logfile
PipeParam(name, visit[, version, outdir, ...])	PipeParam keeps all parameters relevant for the extraction, with default values given for most.
star_bg(starcatfile[, maxrad, shape])	Reads catalogue data on background stars and produces images of stars, to be removed from observations.

Class Inheritance Diagram